Surface-based registration of airborne and terrestrial mobile LiDAR point clouds

Tee-Ann Teo*, Shih Han Huang

*Corresponding author for this work

Research output: Contribution to journalArticlepeer-review

18 Scopus citations


Light Detection and Ranging (LiDAR) is an active sensor that can effectively acquire a large number of three-dimensional (3-D) points. LiDAR systems can be equipped on different platforms for different applications, but to integrate the data, point cloud registration is needed to improve geometric consistency. The registration of airborne and terrestrial mobile LiDAR is a challenging task because the point densities and scanning directions differ. We proposed a scheme for the registration of airborne and terrestrial mobile LiDAR using the least squares 3-D surface registration technique to minimize the surfaces between two datasets. To analyze the effect of point density in registration, the simulation data simulated different conditions and estimated the theoretical errors. The test data were the point clouds of the airborne LiDAR system (ALS) and the mobile LiDAR system (MLS), which were acquired by Optech ALTM 3070 and Lynx, respectively. The resulting simulation analysis indicated that the accuracy of registration improved as the density increased. For the test dataset, the registration error of mobile LiDAR between different trajectories improved from 40 cm to 4 cm, and the registration error between ALS and MLS improved from 84 cm to 4 cm. These results indicate that the proposed methods can obtain 5 cm accuracy between ALS and MLS.

Original languageEnglish
Pages (from-to)12686-12707
Number of pages22
JournalRemote Sensing
Issue number12
StatePublished - 1 Jan 2014


  • Least squares surface matching
  • LiDAR
  • Point clouds
  • Registration


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